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Bioinformatics
Article . 2011 . Peer-reviewed
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Bioinformatics
Article . 2011
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Bioinformatics
Article . 2011
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Fast accessibility-based prediction of RNA–RNA interactions

Authors: Hakim Tafer; Fabian Amman; Florian Eggenhofer; Peter F. Stadler; Ivo L. Hofacker;

Fast accessibility-based prediction of RNA–RNA interactions

Abstract

Abstract Motivation: Currently, the best RNA–RNA interaction prediction tools are based on approaches that consider both the inter- and intramolecular interactions of hybridizing RNAs. While accurate, these methods are too slow and memory-hungry to be employed in genome-wide RNA target scans. Alternative methods neglecting intramolecular structures are fast enough for genome-wide applications, but are too inaccurate to be of much practical use. Results: A new approach for RNA–RNA interaction was developed, with a prediction accuracy that is similar to that of algorithms that explicitly consider intramolecular structures, but running at least three orders of magnitude faster than RNAup. This is achieved by using a combination of precomputed accessibility profiles with an approximate energy model. This approach is implemented in the new version of RNAplex. The software also provides a variant using multiple sequences alignments as input, resulting in a further increase in specificity. Availability: RNAplex is available at www.bioinf.uni-leipzig.de/Software/RNAplex. Contact: htafer@bioinf.uni-leipzig.de; ivo@tbi.univie.ac.at Supplementary information: Supplementary data are available at Bioinformatics Online.

Country
Austria
Related Organizations
Keywords

Models, Molecular, Genome, Base Sequence, 104022 Theoretical chemistry, Sequence Analysis, RNA, 106002 Biochemie, 106002 Biochemistry, 104022 Theoretische Chemie, RNA, Algorithms, Software

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 10%
Top 10%
Top 10%
gold